Xi-he Xie is a Data Scientist II and computational neuroscientist with 9 years of experience translating large-scale neuroimaging and streaming event data into reproducible, production-ready analyses. With a PhD in Computational Neuroscience and a track record at UCSF, Weill Cornell, and The Trade Desk, Xi-he blends probabilistic modeling, GPU-accelerated pipelines, and containerized workflows to move research methods into scalable systems. He has 11 peer-reviewed publications, a fellowship in open science, and a history of organizing interdisciplinary hackathons and teaching data science to researchers. Bilingual in Mandarin and English, he’s an active open-source advocate (once fixing a Jupyter issue) who thrives at the intersection of academic rigor and high-throughput industry data engineering.
9 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy (PhD) Computational Neuroscience, Doctor of Philosophy (PhD) Computational Neuroscience at Joan & Sanford I. Weill Medical College of Cornell University
Bachelor of Science (B.S.) Bioengineering and Biomedical Engineering, Bachelor of Science (B.S.) Bioengineering and Biomedical Engineering at The City College of New York
Visiting Graduate Student Radiology and BioEngineering, Visiting Graduate Student Radiology and BioEngineering at University of California, San Francisco
Contributions:8 releases, 218 commits, 47 PRs in 2 years 9 months
spectralbase-codegraphgraph-model
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